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Amidst the plethora of already-existing and in-use buzzwords, hyper-automation seems like another addition. But if analysts were to be believed, hyper-automation is the next best thing and more and more businesses should start looking into it. That all fine and dandy, but what exactly is it?

Perhaps one reason that has led to hyper-automation being so ambiguous in nature is the fact that it goes by many names. Gartner calls it hyper-automation, IDC calls it Intelligent Process automation and Forrester names the same practices as Digital Process Automation. The problem, however, is that most businesses don’t have a name for it at all.

The Portuguese startup Planless.io made the world’s first hyper-automation tool that was designed to help project management but has yet to present it as the aforementioned businesses insist everyone does. The reason? Most people aren’t aware of the term whatsoever or what it can offer.

Ambiguous Names, But Real

While the debate for its name rages on, its definition is set in stone. Hyper-Automation makes use of a number of tools such as robotic process automation (RPA), artificial intelligence (AI), and intelligent business management software (iBPMS). The goal of hyper-automation is to propel AI-driven decision-making to the next level. Hyper-automation also results in the formation of a DTO or digital twin of the organization. This helps businesses to better visualize functions, processes, and KPIs and how they drive value. In a nutshell, you can see hyper-automation as automated automation where its implementation is often (but not always) at a large scale and functions at high speeds. 

Hyper-automation also allows machines to further automate the implementation of additional automation without needing human input. And if you’re to believe the whispers surrounding its efficacy, it is said that hyper-automation can help machines running it learn 10,000 times faster than their legacy counterparts and can do so without missing it on the next iteration.

But like most new technologies, hyper-automation has yet to make it into the hands of every business. While it is used in some industries, its usage is not widespread. Take call centers and usability testing companies for instance – both parts of an industry that could benefit greatly from hyper-automation but have yet to introduce it to a significant degree.

Examples of Present Usage

Most examples of use-cases of hyper-automation today are in their infancy. This is especially true for contexts where you’d generally expect heavy automation. But what all these use-cases have in common is a focus on accelerating, streamlining and redesigning processes. 

One example is cloud communication where the utilization of RPA and AI is used in call centers. This helps automate some of the more menial tasks like mouse clicks and app launches which are able to pull information from multiple systems to help a client. Normally, when a customer would call in, agents are tasked to aggregate and sift information from multiple systems to get a complete customer profile but with hyper-automation, the entire process of switching between apps is taken out of the equation. This makes the entire process much faster.

The implementation of hyper-automation varies quite a lot and depends in large part on where and why it is employed. That’s likely to stay true for the foreseeable future too. We can expect traditional areas where these AI tools will skyrocket in the next ten years or so include database search querying, CRM, ERP systems, project automation, fulfillment, and tracking of things like leads, processes, people, and packages. As machines learn faster and make fewer mistakes than humans, it’s estimated that the majority of jobs are going to be automated in 20 years or less.

Wyndham Capital Mortgage, which entered a partnership with AI Foundry in May, is another example of a corporation using hyper-automation to automate where automation couldn’t help before. Wyndham Capital Mortgage’s plan is to be a pacesetter within the implementation of automation and, in particular, robotic processing technologies. By implementing [AI Foundry’s] Agile Mortgages’ cognitive robots, the corporation is now ready to push deeper into loan processing stages where document and decision complexity limited automation gains.

In short, Wyndham is speeding up its loan origination process and jacking upscale too. A part of this is achieved by using robots to fetch information from a spread of sources, thereby eliminating menial work typically done by operations employees.

Wyndham Capital Mortgage has been utilizing RPA for a little while now. Integration of AI Foundry’s solutions moves it to hyper-automation. The move to hyper-automation was necessary because RPA on its own is not sufficient to completely automate the loan origination process. Wyndham required a technological fix for RPA’s gaps and shortcomings.

That’s tons of attention for a gaggle of technologies that’s yet to thoroughly settle on a defined name. At present, you may consider hyper-automation to be a smoothly laid foundation for businesses that are keen on future-building instead of future-proofing.

How Does Hyper-Automation Work?

Hyper-automation goes beyond only one piece of software. As such, it entails that companies adopt tools that will be designed to work in conjunction with each other. Hyper-automation’s primary objective is to increase interoperability. This is the convenience at which software can communicate with each other and this is now more critical than ever.

Not only will you like single software solutions that are easy to use and scalable, but you’ll also get to consider how the addition of a tool will work together with your existing methods of operating. Ideally, your goal should be to incorporate tools that act as “plug and play” solutions, which may pull data from different sources and may use APIs to speak to your existing software.

What are the benefits of Hyperautomation?

Speeding Up Complex Work

Hyperautomation gives a high-speed route to engaging everyone in revolutionizing the business, supported by automating more and more complex work that relies on knowledge input from people.

Deploying Digital Workers

Upskilling RPA with intelligence creates an intelligent Digital Workforce which will combat repetitive tasks to reinforce employee performance. These Digital Workers are the change agents of hyper-automation, ready to hook up with various business applications, operate with structured and unstructured data, analyze data and make decisions, and find out processes and new automation opportunities.

Conclusion

Automation and AI will still augment how people work moving forward, so it pays to take a position wisely when selecting these sorts of tools. The benefits and impact of hyper-automation are real. Some of the industries that can look to profit from it are finance, banking, healthcare, manufacturing, life sciences and the public sector – and it doesn’t take a genius to figure out how these encompass most of the industries at play today. So whatever you may call it, its inevitable union into business processes is only a matter of time.